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Non-cooperative games with prospect theory players and dominated strategies

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  • Metzger, Lars Peter
  • Rieger, Marc Oliver

Abstract

We investigate a framework for non-cooperative games in normal form where players have behavioral preferences following Prospect Theory (PT) or Cumulative Prospect Theory (CPT). On theoretical grounds CPT is usually considered to be the superior model, since it normally does not violate first order stochastic dominance in lottery choices. We find, however, that CPT when applied to games may select purely dominated strategies, while PT does not. For both models we also characterize the cases where mixed dominated strategies are preserved and where violations may occur.

Suggested Citation

  • Metzger, Lars Peter & Rieger, Marc Oliver, 2019. "Non-cooperative games with prospect theory players and dominated strategies," Games and Economic Behavior, Elsevier, vol. 115(C), pages 396-409.
  • Handle: RePEc:eee:gamebe:v:115:y:2019:i:c:p:396-409
    DOI: 10.1016/j.geb.2019.04.001
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    References listed on IDEAS

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    1. Marc Rieger & Mei Wang, 2006. "Cumulative prospect theory and the St. Petersburg paradox," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 665-679, August.
    2. Michael Birnbaum, 2005. "A Comparison of Five Models that Predict Violations of First-Order Stochastic Dominance in Risky Decision Making," Journal of Risk and Uncertainty, Springer, vol. 31(3), pages 263-287, December.
    3. Birnbaum, Michael H. & McIntosh, William Ross, 1996. "Violations of Branch Independence in Choices between Gambles," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(1), pages 91-110, July.
    4. Bawa, Vijay S., 1975. "Optimal rules for ordering uncertain prospects," Journal of Financial Economics, Elsevier, vol. 2(1), pages 95-121, March.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    7. Rieger, Marc Oliver, 2014. "Evolutionary stability of prospect theory preferences," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 1-11.
    8. James P. Quirk & Rubin Saposnik, 1962. "Admissibility and Measurable Utility Functions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 29(2), pages 140-146.
    9. Jonathan Shalev, 2000. "Loss aversion equilibrium," International Journal of Game Theory, Springer;Game Theory Society, vol. 29(2), pages 269-287.
    10. Eichberger, Jurgen & Kelsey, David, 2000. "Non-Additive Beliefs and Strategic Equilibria," Games and Economic Behavior, Elsevier, vol. 30(2), pages 183-215, February.
    11. Mei Wang & Paul S. Fischbeck, 2004. "Incorporating Framing into Prospect Theory Modeling: A Mixture-Model Approach," Journal of Risk and Uncertainty, Springer, vol. 29(2), pages 181-197, September.
    12. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    13. Ho-Chyuan Chen & William Neilson, 1999. "Pure-strategy Equilibria with Non-expected Utility Players," Theory and Decision, Springer, vol. 46(2), pages 201-212, April.
    14. Marc Rieger & Mei Wang, 2008. "Prospect theory for continuous distributions," Journal of Risk and Uncertainty, Springer, vol. 36(1), pages 83-102, February.
    15. Kerim Keskin, 2016. "Equilibrium Notions for Agents with Cumulative Prospect Theory Preferences," Decision Analysis, INFORMS, vol. 13(3), pages 192-208, September.
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    3. Zongxian Liu & Wenshuai Song & Bo Cui & Xiaoling Wang & Hongling Yu, 2019. "A Comprehensive Evaluation Model for Curtain Grouting Efficiency Assessment Based on Prospect Theory and Interval-Valued Intuitionistic Fuzzy Sets Extended by Improved D Numbers," Energies, MDPI, vol. 12(19), pages 1-30, September.

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    More about this item

    Keywords

    Prospect theory; Framing; Reference dependent utility; Rank dependent probability weighting; Nash equilibrium; Stochastic dominance; Dominance of strategies;
    All these keywords.

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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